{
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    {
      "cell_type": "code",
      "execution_count": null,
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      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Stitch plots together into a grid\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import pylab as pyl\npyl.ioff()\n\nimport pygeode as pyg\nimport numpy as np\nfrom pygeode.tutorial import t2\n\n\n# Generate some data for a scatter plot\nN = 50\nx_values = np.linspace(-1,1,N)\ncolors = np.random.rand(N)\narea = 1000 * np.random.rand(N) * (1 - abs(x_values))\n\nx = pyg.NamedAxis(values=x_values, name='x')   \ny = pyg.NamedAxis(values=x_values + np.random.rand(N), name='y')\n\nax_scatter = pyg.vscatter(x,y, c=colors, s=area, alpha=0.5)\n\n# Make a vcontour\nax_vcontour = pyg.vcontour(t2.Temp(pres=500, time='10 May 2012')*(pyg.cos(t2.lat))*pyg.sin(t2.lon), cmap='Oranges')\n\n# Stitch the axes together side by side into a grid\nax_both = pyg.plot.grid([[ax_scatter, ax_vcontour]])\n\npyl.ion()\nax_both.render()"
      ]
    }
  ],
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